Given the simplicity of Flask, it seemed like a good match for building APIs. The next thing to find was a "Django REST Framework" for Flask.

!!! check "Inspired **FastAPI** to"
    Be a micro-framework. Making it easy to mix and match the tools and parts needed.

    Have a simple and easy to use routing system.

        {
            "detail": [
                {
                    "type": "string_pattern_mismatch",
                    "loc": ["body", "grant_type"],
                    "msg": "String should match pattern 'password'",
                    "input": "incorrect",
                    "ctx": {"pattern": "password"},
                }
            ]
        }
    ) | IsDict(

If you want to play with JWT tokens and see how they work, check <a href="https://jwt.io/" class="external-link" target="_blank">https://jwt.io</a>.

## Install `python-jose`

        {
            "detail": [
                {
                    "type": "string_pattern_mismatch",
                    "loc": ["body", "grant_type"],
                    "msg": "String should match pattern 'password'",
                    "input": "incorrect",
                    "ctx": {"pattern": "password"},
                }
            ]
        }
    ) | IsDict(

## Add regular expressions

You can define a <abbr title="A regular expression, regex or regexp is a sequence of characters that define a search pattern for strings.">regular expression</abbr> `pattern` that the parameter should match:

=== "Python 3.10+"

    ```Python hl_lines="11"
    {!> ../../../docs_src/query_params_str_validations/tutorial004_an_py310.py!}
    ```

=== "Python 3.9+"

    ```Python hl_lines="11"

        {
            "detail": [
                {
                    "type": "string_pattern_mismatch",
                    "loc": ["body", "grant_type"],
                    "msg": "String should match pattern 'password'",
                    "input": "incorrect",
                    "ctx": {"pattern": "password"},
                }
            ]
        }
    ) | IsDict(

Let's put that data in the Pydantic `UserInDB` model first.

You should never save plaintext passwords, so, we'll use the (fake) password hashing system.

If the passwords don't match, we return the same error.

#### Password hashing

"Hashing" means: converting some content (a password in this case) into a sequence of bytes (just a string) that looks like gibberish.

That, plus the simple fact that Python is the main language for **Data Science**, Machine Learning and especially Deep Learning, make FastAPI a very good match for Data Science / Machine Learning web APIs and applications (among many others).

To see how to achieve this parallelism in production see the section about [Deployment](deployment/index.md){.internal-link target=_blank}.